Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/15428#discussion_r83911537
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
---
@@ -83,10 +83,20 @@ class QuantileDiscretizerSuite
.setOutputCol("result")
.setNumBuckets(numBuckets)
- // Reserve extra one bucket for NaN
- val expectedNumBuckets = discretizer.fit(df).getSplits.length - 1
- val result = discretizer.fit(df).transform(df)
- val observedNumBuckets = result.select("result").distinct.count
+ // Reserve extra one bucket for NaN values
+ discretizer.setHandleInvalid("keep")
+ var expectedNumBuckets = discretizer.fit(df).getSplits.length - 1
--- End diff --
I'd also recommend directly testing the values of the splits. The current
test makes sure that handleInvalid is passed to the bucketizer correctly, which
is important but separate.
Also, please use vals (not vars) for clarity. I'd recommend making a
helper method for lines 87-93, which can be reused for the test of
handleInvalid = "skip"
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